@article{Wu_Feng Teng_Lindsay_2022, place={Melbourne, Australia}, title={Challenges in a mobile English telecollaborative project: Towards a conceptual model}, volume={38}, url={https://ajet.org.au/index.php/AJET/article/view/6371}, DOI={10.14742/ajet.6371}, abstractNote={<p>This paper, drawing upon a mobile telecollaborative project, resonates with the rapid development of technology in language learning. We employed the instant messaging app WeChat to create an English telecollaborative environment for two groups of Chinese students to communicate within. Interview data were triangulated with students’ chat transcripts and comments from a teacher’s reflective journal. A mixed-methods approach, including quantitative descriptive analysis, thematic analysis and content analysis, was used to investigate the challenges and the linguistic performance by applying the community of inquiry framework to the students’ chats. The analysis illustrates some of the complexities and challenges of using online apps as a way of communicating in a second language: students expected more teacher support, they struggled to use the app due to their physical environments and they felt that they were not sufficiently well prepared for chatting in an English medium environment. Based on the findings, a conceptual model is proposed for consideration when encouraging students to engage in telecollaborative learning.</p> <p><em>Implications for practice or policy:</em></p> <ul> <li>Teachers should enhance their visibility in mobile telecollaborative projects by promoting participants’ contribution through different facilitation techniques.</li> <li>Teachers and educators can capitalise on the proposed conceptual model to guide their own design of such online learning experiences for their learners.</li> <li>Telecollaborative learning can be improved by taking into account various factors such as physical environment, the medium of communication and the potential incentives.</li> </ul>}, number={1}, journal={Australasian Journal of Educational Technology}, author={Wu, Junjie Gavin and Feng Teng, Mark and Lindsay, Miller}, year={2022}, month={Jan.}, pages={1–19} }